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Leveraging Artificial Intelligence has transitioned from a novel idea to a crucial growth strategy in fast-paced B2B marketing. Drawing from my experiences with startups like Productboard, Segment, Grammarly, and Vowel, I've seen firsthand how AI can revolutionize product marketing. This article delves into how B2B marketing teams can and should use AI better today, specifically in product marketing throughout the product lifecycle.

Before diving into how these tools can enhance your marketing efforts, it's essential to have a sound marketing strategy in place. AI tools are powerful, but they cannot replace a well-thought-out strategy. Here are a few critical components you need to establish first:

• Clear Ideal Customer Profile (ICP) and Target Personas: Understand your ideal customers and develop detailed personas to guide your marketing efforts.
• Messaging, Positioning, and Branding: Develop strong messaging, clear positioning, and consistent branding to ensure your content and communication resonate with your target audience.
• Adequate Customer Feedback: Make it a habit to gather and review substantial customer feedback to inform your product and marketing decisions.
• Example Content and Metrics: Provide example content, relevant metrics, and detailed outlines to guide AI tools in generating high-quality content.
• Data Tracking Tools: Create a customer data infrastructure and use tools like Segment to collect, transform, and send your first-party data. This simplifies data collection and integration, allowing you to focus more on utilizing your data rather than gathering it.

You can't just go in blank and expect these AI solutions to do all the work. You need to have your marketing strategy first and then use tools to supplement it or scale your efforts. Don't accept anything blindly; proofread, revise, review, and look at the data.

My Favorite AI Solutions to Product Marketing Challenges

1. Runic: Enhancing Marketing Intelligence

Problem:

Traditional marketing platforms often provide generic insights, even with ChatGPT integrations. These insights aren't actionable for teams, leading to inefficiencies and missed opportunities. This lack of actionable insights means marketing teams struggle to make data-driven decisions, impacting the effectiveness of their campaigns and overall strategy. Consequently, companies cannot fully understand their market position and customer preferences, leading to suboptimal marketing performance.

Solution:

‍Runic offers advanced marketing intelligence that empowers teams with data-driven insights. By utilizing AI to analyze market trends, customer behavior, and competitive landscapes, Runic provides actionable intelligence that can shape product marketing strategies. This enables marketing teams to make informed decisions that enhance campaign effectiveness and drive growth. By offering deep insights into customer and market behavior, Runic helps companies stay ahead of the competition and meet their customers' needs more effectively.

My Experience:

Combining external and internal data is a game-changer, but actually having real recommendations on what content to create and which product improvements to focus on really helps drive marketing excellence. With Runic, I can now create content and strategies directly informed by comprehensive data, making my efforts more effective and impactful.

Example Use Case:

A large SaaS company uses Runic to evaluate its partnerships. They want to see which partners have the best reputation among developers and watch how that's changing week after week. This will help inform the product marketing team about how to message around partnerships — which to avoid and which to promote. They're using public data right now, but they could easily integrate support tickets and check which partners appear problematic.

Runic automatically recommends strategies based on their goals and existing partnerships.

Caution:

Ensure you have a robust data infrastructure and clear objectives before integrating Runic. The tool is most effective when it can access comprehensive and relevant data to analyze.

2. Enterpret: Gaining Customer Feedback for Product Decisions

Problem:

Many products fail to meet customer expectations because decisions are made without adequate customer feedback. Studies show that 69% of products are not well-received due to this disconnect. This gap in understanding customer needs leads to developing features and products that do not align with user expectations, resulting in high churn rates and wasted resources. Without a systematic approach to gathering and analyzing customer feedback, businesses risk alienating their customer base and missing out on crucial opportunities for improvement.

Solution:

‍Enterpret is an AI-driven platform that aggregates and analyzes customer feedback to inform product decisions and ensure products align with customer needs. By continuously collecting and interpreting feedback, Enterpret helps companies understand and align with their customer's preferences and pain points. This proactive approach enables businesses to make data-driven product decisions that enhance customer satisfaction and loyalty. Furthermore, by identifying trends and common feedback themes, Enterpret helps companies prioritize their development efforts on features that will have the most significant impact.

My Experience:

Understanding what customers wanted previously took me hours, combining and analyzing endless sheets and emails from hundreds of sales and customer success individuals. With Enterpret, I can see clear and actionable customer feedback, efficiently guiding features for the product roadmap. This has saved me time and significantly improved how the products I market align with customer expectations.

Example Use Case:

Apollo, a leading sales engagement platform, uses Enterpret to gather and analyze customer feedback across various channels. This feedback informs product development and marketing strategies, helping Apollo better understand and address user pain points. This data-driven approach has resulted in improved user satisfaction and increased revenue.

Caution:

Ensure you have established channels for collecting customer feedback and a team ready to act on the insights provided by Enterpret. The tool's effectiveness depends on your priority to action the feedback it provides.

3. Pepper Content: Optimizing Content Marketing for Product Launches & Customer Acquisition

Problem:

Creating engaging and compelling content for product launches and updates is a resource-intensive process that can be difficult to scale. Without the ability to quickly produce high-quality content, companies struggle to maintain consistent communication with their audience, affecting brand awareness and customer engagement. This bottleneck in content production can delay marketing campaigns and reduce their overall impact, making it challenging for companies to achieve their growth objectives.

Solution:

‍Pepper Content combines human expertise with AI to enhance content marketing efforts, particularly during product launches and for customer acquisition. The platform helps create compelling content that resonates with target audiences and drives engagement. By leveraging AI to streamline content creation processes, Pepper Content enables companies to scale their marketing efforts efficiently. This hybrid approach ensures that content is produced faster, highly relevant, and tailored to the audience's interests, leading to better engagement and conversion rates.

My Experience:

I’ve always written my own blog posts, but I'm excited to try Pepper Content. I would never want to rely solely on AI or solely on a human, but having both in the mix would be ideal. The combination of human intelligence and AI efficiency could elevate the quality and reach of my content while saving me time.

Example Use Case:

Naukri.com, a job portal company, used Pepper Content to manage its extensive content needs.

Pepper Content helped Naukri.com create detailed blog posts, social media updates, and email campaigns for product launches. The AI analyzed what content formats and messages performed best, ensuring each piece of content effectively drove engagement and conversions. This strategy significantly boosted Naukri.com's customer acquisition efforts.

Caution:

While AI can significantly speed up content creation, ensure you maintain a balance between AI-generated and human-crafted content to keep your brand voice authentic and engaging. Always provide detailed outlines, sample high-performing content, and review the content output provided.

4. UnSurvey: Scaling Sales Enablement & Competitive Analysis

Problem:

Gathering and analyzing information at scale is time-consuming and challenging. For example, understanding why deals are won or lost is critical, yet traditional methods often rely on limited data from a handful of interviews. This limited feedback scope can lead to skewed insights and an incomplete understanding of customer objections and competitive dynamics. Without comprehensive win/loss analysis, sales teams may miss critical patterns and fail to address key issues that affect their success rates, resulting in lost opportunities and revenue.

Solution:

‍UnSurvey uses AI to scale survey and data collection. It creates personalized conversational agents to gather and analyze information at scale, providing comprehensive insights from hundreds of interactions. This can help with win/loss analysis and other use cases, providing comprehensive insights. By conducting dynamic and personalized voice and text conversations at scale, UnSurvey transforms feedback collection into engaging interactions, helping teams refine their strategies. Businesses gain high-quality insights from a broad sample of interactions, leading to more accurate and actionable data. With UnSurvey, companies can better understand the reasons behind their sales outcomes and make data-driven adjustments to improve their win rates.

My Experience:

Creating Win/Loss notes and other surveys was previously time-consuming and not scalable. With UnSurvey, I can quickly understand win/loss reasons, helping PMs improve the product and drive improved sales. This scalability and accuracy of feedback collection are game-changers for refining our strategies.

Example Use Case:

A hypothetical example could be HubSpot, a leading CRM and marketing platform, using UnSurvey to gather extensive feedback on why specific deals are lost to competitors. The AI-driven insights help HubSpot understand common objections and competitive threats, allowing it to improve its sales pitches and product offerings. This data-driven approach significantly enhances their win rates and sales strategy.

Caution:

To get the most out of UnSurvey, ensure you have a workflow set up that quickly and automatically gets the Survey into the hands of customers won and lost. Don't manually send the Survey out — UnSurvey should make your life easier, not add more work! You don't want to wait days, or the data and insights won't be great.

5. TofuHQ: Your AI-Powered B2B Marketing Sidekick

Problem:

B2B marketing teams face the challenge of efficiently scaling content creation and personalizing go-to-market (GTM) strategies for diverse personas, industries, and accounts. This includes effectively repurposing content across various channels and formats, often leading to underutilized resources and budgets due to manual processes.

Solution:

‍TofuHQ harnesses AI as an automated marketing playbook, enabling teams to generate and scale hyper-personalized marketing campaigns across all channels. This “AI Content Factory” facilitates creating, personalizing, and repurposing content for marketing emails, SDR sequences, landing pages, white papers, ebooks, case studies, sales decks, blog posts, ad campaigns, and social posts. It ensures that all content is consistently on-brand and on-message, automates the publication process on native channels, and enables real-time performance analysis to optimize campaigns dynamically.

My Experience:

Previously, creating new landing pages for campaigns took me hours, especially for different audiences and use cases in paid social and digital campaigns. Updating 20 landing pages with other priorities would have taken me months. With TofuHQ, I can quickly create multiple landing pages tailored to specific audiences. This gives me significant efficiencies while maintaining my brand voice, messaging, and company positioning—a game-changer.

Example Use Case:

Golioth, a platform for managing IoT devices, utilizes TofuHQ to optimize landing pages for different customer segments. By using AI to test various headlines, images, and calls to action, Golioth can identify the most effective combinations, thus improving lead conversion rates and reducing customer acquisition costs. This method is pivotal in refining their online marketing strategy and boosting their sales pipeline. Moreover, TofuHQ aids Golioth in scaling its marketing efforts and generating hyper-personalized campaigns across multiple channels, significantly enhancing overall reach and engagement.

Caution:

The more information you provide to TofuHQ, the better it performs. Be sure to share your brand messaging, positioning, voice, and sample content. Additionally, always review any AI outputs to ensure they align with your expectations.

6. Daydream: AI Insights and Reporting for GTM Teams

Problem:

Go-to-market teams often find it challenging to synthesize data from various sources into actionable insights that inform their strategies. This data fragmentation can lead to missed opportunities and inefficient decision-making, hindering the effectiveness of marketing and sales initiatives. Without a unified view of critical metrics, GTM teams may struggle to align their efforts and optimize their strategies for maximum impact.

Solution:

‍Daydream provides AI-driven insights and reporting for go-to-market (GTM) teams, helping them make informed decisions quickly. The platform synthesizes data from various sources to deliver actionable insights.

Daydream enables GTM teams to track critical metrics and adjust their strategies in real-time by providing a comprehensive and unified view of marketing performance. This holistic approach ensures that all marketing and sales strategy aspects are aligned and optimized for success, leading to improved efficiency and better business outcomes.

My Experience:

I've always wanted a tool like Daydream. Not having self-serve data or waiting for data analysts/engineers to build Looker dashboards often took weeks, forcing me to make marketing decisions with incomplete data or rely on SQL queries. With Daydream, I can easily see trends with my data in a presentable way that’s easy to understand and share with senior leaders. The templates are a lifesaver, providing a straightforward way and structured process to track key metrics and performance indicators. It’s truly a game-changer.

Example Use Case:

‍Daydream’s "SaaS Marketing Performance" template helps SaaS companies build a profitable marketing engine by tracking performance throughout the sales funnel. This template enables companies to monitor key metrics and adjust their real-time strategies. For instance, a SaaS company can use Daydream to track how marketing activities influence conversions and customer retention. It provides a comprehensive view of their marketing effectiveness.

Caution:

To get the best results from Daydream, ensure you’re effectively capturing your data sources and that your team is trained to act on the insights provided. Regularly review and update your data inputs to keep the analyses relevant and accurate.

Integrating AI into the Product Marketing Lifecycle

Integrating AI into the product marketing lifecycle is not just about adopting new tools but transforming how teams operate. Here's how B2B startups can leverage AI at different stages of their product marketing:

1. Market Research and Intelligence. During the initial stages of product development, AI tools like Runic can analyze vast datasets to identify market opportunities and customer needs. This intelligence shapes the product's features and positioning, ensuring it meets actual market demands.
2. Customer Feedback and Product Iteration. Once a product is in development or launched, platforms like Enterpret become essential. Continuous feedback collection and analysis ensure that the product evolves based on actual user experiences and preferences, leading to higher customer satisfaction and retention.
3. Content Creation and Distribution. AI tools like Pepper Content streamline content creation for product launches and updates. AI helps teams craft effective marketing campaigns that drive engagement and conversions by understanding what content formats and messages resonate with the target audience.
4. Sales and Marketing Optimization. During the sales process, UnSurvey provides deep insights into win/loss scenarios, enabling teams to refine their strategies. Meanwhile, TofuHQ scales landing pages and other content, ensuring every potential customer has a high chance of converting, enhancing the overall effectiveness of marketing efforts.
5. Go-to-Market Strategy and Execution. Finally, tools like Daydream offer comprehensive insights and reporting, enabling GTM teams to make data-driven decisions. This holistic view ensures that all aspects of the marketing strategy are aligned and optimized for success.

Conclusion

AI is not a silver bullet but a powerful enabler that can transform B2B product marketing from reactive to proactive, from generic to highly personalized. By integrating AI tools like Runic, Enterpret, Pepper Content, UnSurvey, TofuHQ, and Daydream, startups can enhance their marketing strategies at every product lifecycle stage. These tools provide the insights and efficiencies needed to create products that meet market demands and exceed customer expectations.

In a world where 69% of products fail to resonate with customers, leveraging AI to understand, engage, and delight users is not just advantageous—it's essential. For B2B startups navigating the competitive landscape, AI-driven product marketing can be the differentiator that propels them to success.

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About the Author

Cindy Berman is a seasoned product marketing and growth leader with extensive experience guiding startups like Segment, Productboard, Grammarly, and Vowel. With a deep understanding of the AI landscape, Cindy is dedicated to helping businesses leverage AI to achieve their marketing goals. She holds an MBA from Wharton and is an active angel investor, having made 17 investments, many of which leverage AI.

About RevelOne

RevelOne is a leading go-to-market advisory and recruiting firm. We help hundreds of VC/PE-backed companies each year leverage the right resources to achieve more profitable growth. We do 250+ retained searches a year in Marketing and Sales roles from C-level on down for some of the most recognized names in tech. In addition to our Search Practice, our Interim Expert Network includes 200+ vetted expert contractors – executive-level leaders and head-of/director-level functional experts – available for interim or fractional engagements. For help in any of these areas, contact us.